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AMS Weekly Seminar | Assistant Professor Jeremias Sulam

April 25 @ 1:30 pm - 2:30 pm

Location: Olin 305

When: April 25th at 1:30 p.m.

Title: Yay, my deep network works! But.. what did it learn?

Abstract: Modern machine learning methods are revolutionizing what we can do with data — from tiktok video recommendations to biomarker discovery in cancer research. Yet, the complexity of these deep models makes it harder to understand what functions these data-dependent models are computing, and which features they learn to be important for a given task. In this talk, I will review two approaches for turning general deep learning models more interpretable, both in an unsupervised setting in the context of imaging inverse problems, as well as in supervised classification problems for computer vision.

Bio: Jeremias Sulam received his bioengineering degree from Universidad Nacional de Entre Ríos, Argentina, in 2013, and his PhD in Computer Science from the Technion – Israel Institute of Technology, in 2018. He joined the Biomedical Engineering Department at Johns Hopkins University in 2018 as an assistant professor, and he is also a core faculty at the Mathematical Institute for Data Science (MINDS) and the Center for Imaging Science at JHU. He is the recipient of the Best Graduates Award of the Argentinean National Academy of Engineering, and the Early CAREER award of the National Science Foundation. His research interests include inverse problems, sparse representation modeling and machine learning.

Zoom link: https://wse.zoom.us/j/94601022340

Details

Date:
April 25
Time:
1:30 pm - 2:30 pm
Event Category:

Venue

Olin 305